CFD Simulations AC7-02
Airflow in the human upper airways
Application Challenge AC7-02 © copyright ERCOFTAC 2020
CFD Simulations
Overview of CFD Simulations
Three LES (LES1-3) and one RANS simulation were carried out in the benchmark geometry at an air flowrate of 60 L/min.
This flowrate results in a Reynolds number of 4921 in the model’s trachea.
This is slightly higher than the Reynolds number in the experiments, due to the reasons discussed in section 2.4.
The details of the numerical tests are given in the following paragraphs.
In summary, the main differences between the simulations are:
1. Computational meshes: LES1&2 employ the same comp. meshes, whereas LES3 and RANS use different meshes.
2. Turbulence modeling: LES1 uses the dynamic version of the Smagorinsky-Lilly subgrid scale model, whereas LES2&3 employ the Wall-adapting eddy viscosity (WALE) SGS model.
In RANS simulations, the k-ω SST, standard k-ε and RNG k-ε turbulence model have been tested.
3. Discretisation method: LES1&2 and RANS use the Finite Volume approach whereas LES3 employs the Finite Element Method.
Large Eddy Simulations — Case LES1
Computational domain and meshes
The geometry used in the calculations is the same as the one used in the experiments developed by the group at Brno University of Technology (BUT). The computational domain, shown in Fig. 8, has one inlet and ten different outlets, for which appropriate boundary conditions must be specified in the simulations.
The digital model of the physical geometry was used to generate a proper computational mesh in order to perform the simulations.
For LES1, two meshes were generated to allow us to examine the sensitivity of the results to the mesh resolution.
The coarser mesh includes 10 million computational cells and the finer approximately 50 million cells.
In these meshes, the near-wall region was resolved with prismatic elements, while the core of the domain was meshed with tetrahedral elements.
Cross-sectional views of these meshes at seven stations are shown in Fig. 9.
A grid convergence analysis was carried out in order to determine the appropriate resolution for the simulations.
This analysis is presented in section 3.2.3.
Table 3 reports grid characteristics, such as the height of the wall-adjacent cells (), the number of prism layers near the walls, the average expansion ratio of the prism layers (), the total number of computational cells, the average cell volume (V) and the average and maximum y+ values.
The higher y+ values (above 1) are found near the glottis constriction and the bifurcation carinas, which are characterised by high wall shear stresses.
Solution strategy and boundary conditions — Airflow
Numerical accuracy
Large Eddy Simulations — Case LES2
Computational domain and meshes
Solution strategy and boundary conditions — Airflow
Numerical accuracy
Large Eddy Simulations — Case LES3
Computational domain and meshes
Solution strategy and boundary conditions — Airflow
Numerical accuracy
RANS Simulations
Computational domain and meshes
Solution strategy and boundary conditions — Airflow
Numerical accuracy
Contributed by: P. Koullapisa, J. Muelab, O. Lehmkuhlc, F. Lizald, J. Jedelskyd, M. Jichad, T. Jankee, K. Bauere, M. Sommerfeldf, S. C. Kassinosa —
aDepartment of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
bHeat and Mass Transfer Technological Centre, Universitat Politècnica de Catalunya, Terrassa, Spain
cBarcelona Supercomputing center, Barcelona, Spain
dFaculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic
eInstitute of Mechanics and Fluid Dynamics, TU Bergakademie Freiberg, Freiberg, Germany
fInstitute Process Engineering, Otto von Guericke University, Halle (Saale), Germany
© copyright ERCOFTAC 2020